LLM on FHIR - Demystifying Health Records "Demystifying Health Records - A Conversational Interface to Your Health Data" This repository contains the LLM on FHIR Application to demonstrate the power of LLMs to explain and provide helpful context around patient data provided in the FHIR format. It...
2. Large Language Models (LLMS) with MATLAB As a programmer, I have more fun with LLMS when I can interact with them programmatically. That's wherethis MathWorks repositorycomes in. It contains code to connect MATLAB to theOpenAI® Chat Completions API(which powers ChatGPT™), OpenAI Im...
To incorporate adaptation into serious games in a systematic way, we employ the MAPE-K loop framework. A key focus is the inclusion of educators in the adaptation process, who ensure that AI-driven changes align with educational goals. We thus propose an architecture that integrates player/...
This repo demonstrates an implementation of an AI Instructor using LLMs. I leverage the langchain library in this implementation and are inspired by CAMEL architecture . Overview The AI Instructor project aims to revolutionize the way people learn by harnessing the power of artificial intelligence. ...
Pros of Running LLMs Locally Cons of Running LLMs Locally Factors to Consider When Choosing a Deployment Strategy for LLMs Conclusion Share In recent months, we have witnessed remarkable advancements in the realm of Large Language Models (LLMs), such as ChatGPT, Bard, and LLaMA, which h...
You can interact with supported large language models using the AI Playground. The AI Playground is a chat-like environment where you can test, prompt, and compare LLMs. This functionality is available in your Databricks workspace.Requirements...
However, challenges persist in handling domain-specific tasks, leading to the development of the Retrieval-Augmented Generation (RAG) framework. RAG enhances LLMs by integrating external data retrieval, enriching their contextual understanding, and expanding their knowledge base beyond pre-existing training...
Fine-tuning LLMs leverages the vast knowledge acquired by LLMs and tailors it towards specialized tasks. Imagine an LLM pre-trained on a massive corpus of text.
Prompt Content turns video insights accessible for LLMs and text encoders. This feature empowers VI users to ground LLMs to video archives for semantic search and summarization scenarios. Chapters 00:00 - Introduction 00:17 - On today's episode 00:50 - Overview of Video AI Indexer 01:51 ...
Awesome papers about generative Information extraction using LLMs The organization of papers is discussed in our survey: Large Language Models for Generative Information Extraction: A Survey. If you find any relevant academic papers that have not been included in our research, please submit a request...